Optimized Non-Regenerative MIMO Relaying (ONEMORE)

• Applicant: Professor Dr.-Ing. Eduard Axel Jorswieck
• Subject Area: Electronic Semiconductors, Components and Circuits, Integrated Systems, Sensor Technology, Theoretical Electrical Engineering
• Term: from 2014 to 2015
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 264858293

MIMO relay network models have been widely used in researches and applications for future mobile communications. This gives an impetus to the investigations of the fundamental limits of the general MIMO relay networks. Also, degree of freedom (DoF) is an important index of a network, which scales linearly with the sum rate in high signal-to-noise-ratio (SNR) scenarios. In our project, we plan to optimize the achievable sum rate and the achievable DoFs of non-regenerative MIMO relay networks for finite SNR operating points, through both theoretical analysis and efficient algorithms.First, we build up two types of models: sum rate maximization models with power constraints and sum transmit power minimization models with rate constraints. The main difficulty to optimize the system is that the sum rate expression is complicated and highly nonlinear. In the project, the sum rate will be approximated by several approaches, and their results compared. Nonlinear optimization techniques are applied to solve the resulting nonconvex nonlinear matrix optimization problems. The computational complexity and their signalling overhead of the algorithms will be analyzed. Based on the models and the corresponding algorithms, we will obtain the system achievable rate region and the power region. To achieve high sum rate, we plan to design two types of data stream selection algorithms: the optimization technique approach with a series of nonlinear optimization subproblems and the heuristic greedy approach with stream selection criteria. The works of our project will not only enhance the theoretical results, but also provide guidelines to applications of non-regenerative MIMO relay networks.

• DFG Programme: Research Grants